Machine Learning with Python: from Linear Models to Deep Learning

Regina Barzilay, Tommi Jaakkola, Karene Chu, MITx

An in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects. -- Course 4 of 4 in the MITx MicroMasters program in Statistics and Data Science.

Machine learning methods are commonly used across engineering and sciences, from computer systems to physics. Moreover, commercial sites such as search engines, recommender systems (e.g., Netflix, Amazon), advertisers, and financial institutions employ machine learning algorithms for content recommendation, predicting customer behavior, compliance, or risk.

As a discipline, machine learning tries to design and understand computer programs that learn from experience for the purpose of prediction or control.

In this course, students will learn about principles and algorithms for turning training data into effective automated predictions. We will cover:

  • Representation, over-fitting, regularization, generalization, VC dimension;
  • Clustering, classification, recommender problems, probabilistic modeling, reinforcement learning;
  • On-line algorithms, support vector machines, and neural networks/deep learning.

Students will implement and experiment with the algorithms in several Python projects designed for different practical applications.

This course is part of theMITx MicroMasters Program in Statistics and Data Science. Master the skills needed to be an informed and effective practitioner of data science. You will complete this course and three others from MITx, at a similar pace and level of rigor as an on-campus course at MIT, and then take a virtually-proctored exam to earn your MicroMasters, an academic credential that will demonstrate your proficiency in data science or accelerate your path towards an MIT PhD or a Master's at other universities. To learn more about this program, please visit https://micromasters.mit.edu/ds/.

If you have specific questions about this course, please contact us atsds-mm@mit.edu.

What will you learn

  • Understand principles behind machine learning problems such as classification, regression, clustering, and reinforcement learning
  • Implement and analyze models such as linear models, kernel machines, neural networks, and graphical models
  • Choose suitable models for different applications
  • Implement and organize machine learning projects, from training, validation, parameter tuning, to feature engineering.

会期:
  • 2020年2月03日
介绍:
  • 免费:
  • 收费:
  • 证书:
  • MOOC:
  • 视频讲座:
  • 音频讲座:
  • Email-课程:
  • 语言: 英语 Gb

反馈

目前这个课程还没有反馈。您想要留第一个反馈吗?

请注册, 为了写反馈

Show?id=n3eliycplgk&bids=695438
NVIDIA
还有这个题目的:
Small-icon.hover Introduction to Data Science
Join the data revolution. Companies are searching for data scientists. This...
Gears-818461_1280 Machine Learning Capstone: An Intelligent Application with Deep Learning
Have you ever wondered how a product recommender is built? How you can infer...
D6b3439e-b8ca-4b80-bb97-24847723b78b-cd9d4fe0a8b2.small Introduction to Predictive Analytics
In the age of Big Data, businesses need predictive analysts to help them excel...
Ac499cd6-a3ac-4a5f-a307-bb28ea318de1-bfbe5ace0b55.small Machine Learning Fundamentals
Understand machine learning’s role in data-driven modeling, prediction...
还有标题«计算机科学»:
695ff980-b45a-425f-bee6-51bf6e962d90-de2d1a1c22e0.small Video Game Design History
Learn about the evolution of video games from experts at The Strong National...
595aa0b6-077d-439b-a651-95a9ee65c51a-fc966dc2648f.small Video Game Design and Balance
Learn about the video game design process and experiment with effective methods...
Fcd236ea-68ae-46f7-b991-849a41cebc64-0ea84acf6bad.small Video Game Asset Creation and Process
Learn about the tools, processes and platforms that allow video game assets...
Regular_7e290d30-8e84-46b2-bf50-801246fb157c Advanced Data Mining with Weka
Learn how to use popular packages that extend Weka's functionality and areas...
Regular_0b883f52-bc27-40f6-b633-d5fa9dd1101a Prepare to Run a Code Club
Build your confidence and get practical advice on launching and running a Code...
还有edX:
4178fda1-e8c7-476c-81e8-8a6b453a6a76-569208c21635.small Humanitarian Response to Conflict and Disaster
Learn the principles guiding humanitarian response to modern emergencies, and...
695ff980-b45a-425f-bee6-51bf6e962d90-de2d1a1c22e0.small Video Game Design History
Learn about the evolution of video games from experts at The Strong National...
595aa0b6-077d-439b-a651-95a9ee65c51a-fc966dc2648f.small Video Game Design and Balance
Learn about the video game design process and experiment with effective methods...
Fcd236ea-68ae-46f7-b991-849a41cebc64-0ea84acf6bad.small Video Game Asset Creation and Process
Learn about the tools, processes and platforms that allow video game assets...
A3940ac0-0757-4181-8b9d-5741f8a934fc-87e2da858ee6.small Minds and Machines
An introduction to philosophy of mind, exploring consciousness, reality, AI...

© 2013-2019